Compare the Top Data Science Software for Linux as of April 2025

What is Data Science Software for Linux?

Data science software is a collection of tools and platforms designed to facilitate the analysis, interpretation, and visualization of large datasets, helping data scientists derive insights and build predictive models. These tools support various data science processes, including data cleaning, statistical analysis, machine learning, deep learning, and data visualization. Common features of data science software include data manipulation, algorithm libraries, model training environments, and integration with big data solutions. Data science software is widely used across industries like finance, healthcare, marketing, and technology to improve decision-making, optimize processes, and predict trends. Compare and read user reviews of the best Data Science software for Linux currently available using the table below. This list is updated regularly.

  • 1
    Dataiku

    Dataiku

    Dataiku

    Dataiku is an advanced data science and machine learning platform designed to enable teams to build, deploy, and manage AI and analytics projects at scale. It empowers users, from data scientists to business analysts, to collaboratively create data pipelines, develop machine learning models, and prepare data using both visual and coding interfaces. Dataiku supports the entire AI lifecycle, offering tools for data preparation, model training, deployment, and monitoring. The platform also includes integrations for advanced capabilities like generative AI, helping organizations innovate and deploy AI solutions across industries.
  • 2
    Stata

    Stata

    StataCorp LLC

    Stata delivers everything you need for reproducible data analysis—powerful statistics, visualization, data manipulation, and automated reporting—all in one intuitive platform. Stata is fast and accurate. It is easy to learn through the extensive graphical interface yet completely programmable. With Stata's menus and dialogs, you get the best of both worlds. You can easily point and click or drag and drop your way to all of Stata's statistical, graphical, and data management features. Use Stata's intuitive command syntax to quickly execute commands. Whether you enter commands directly or use the menus and dialogs, you can create a log of all actions and their results to ensure the reproducibility and integrity of your analysis. Stata also has complete command-line scripting and programming facilities, including a full matrix programming language. You have access to everything you need to script your analysis or even to create new Stata commands.
    Starting Price: $48.00/6-month/student
  • 3
    JetBrains Datalore
    Datalore is a collaborative data science and analytics platform aimed at boosting the whole analytics workflow and making work with data enjoyable for both data scientists and data savvy business teams across the enterprise. Keeping a major focus on data teams workflow, Datalore offers technical-savvy business users the ability to work together with data teams, using no-code or low-code together with the power of Jupyter notebooks. Datalore enables analytical self-service for business users, enabling them to work with data using SQL and no-code cells, build reports and deep dive into data. It offloads the core data team with simple tasks. Datalore enables analysts and data scientists to share results with ML Engineers. You can run your code on powerful CPUs or GPUs and collaborate with your colleagues in real-time.
    Starting Price: $19.90 per month
  • 4
    Coder

    Coder

    Coder

    Coder delivers self-hosted cloud development environments consistently provisioned as code and pre-deployed for developer activity on day one. Preferred by enterprises, Coder is open source and runs air-gapped on-premise or in your cloud, giving developers access to powerful infrastructure without compromising governance. Coder moves local development and source code to your centralized infrastructure where developers can access their remote environments via their favorite desktop or web-based IDE. This is the optimal intersection of improved developer experience, productivity, and security. Coder’s ephemeral development environments are provisioned as code from pre-defined templates, which means developers can create a new workspace with a click. Now, they can avoid days or weeks struggling with local dependency versioning conflicts or security approvals. With Coder, developers can onboard or shift between projects in minutes.
  • 5
    SAS Visual Statistics
    With SAS Visual Statistics, multiple users can explore data, then interactively create and refine predictive models. Your data scientists and statisticians can act on observations at a granular level using the most appropriate analytical modeling techniques. The result? You'll unearth insights at unprecedented speeds, and find new ways to grow revenue. Easily build and refine models to target specific groups or segments, and run numerous scenarios simultaneously. You can ask more what-if questions to get better results. And put results into action with an automatically generated score code. Empower multiple users to interact with data visually – to add or change variables, remove outliers, etc. Instantly see how changes affect your model's predictive power, and make refinements quickly. Data science teams have the ultimate flexibility of working in their language of choice, so they can use their skills to the fullest. SAS Visual Statistics unites all analytical assets.
  • 6
    SAS Viya
    SAS® Viya® data science offerings provide a comprehensive, scalable analytics environment that's quick and easy to deploy, enabling you to meet diverse business needs. Automatically generated insights enable you to identify the most common variables across all models, the most important variables selected across models and assessment results for all models. Natural language generation capabilities are used to create project summaries written in plain language, enabling you to easily interpret reports. Analytics team members can add project notes to the insights report to facilitate communication and collaboration among team members. SAS lets you embed open source code within an analysis and call open source algorithms seamlessly within its environment. This facilitates collaboration across your organization because users can program in their language of choice. You can also take advantage of SAS Deep Learning with Python (DLPy), our open-source package on GitHub.
  • 7
    Amadea

    Amadea

    ISoft

    Amadea technology relies on the fastest real-time calculation and modeling engine on the market. Speed up the creation, deployment and automation of your analytics projects within the same integrated environment. Data quality is the key to analytical projects. Thanks to the ISoft real-time calculation engine, the fastest on the market, Amadea allows companies to prepare and use massive and/or complex data in real-time, regardless of the volume. ISoft started from a simple observation, successful analytical projects must involve the business users at every stage. Founded on a no-code interface, accessible to all types of users, Amadea allows everyone involved in analytical projects to take part. As Amadea has the fastest real-time calculation engine on the market, it lets you specify, prototype and build your data applications simultaneously. Amadea incorporates the fastest real-time data analysis engine on the market, 10 million lines per second & per core for standard calculations.
  • Previous
  • You're on page 1
  • Next